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3

I can give you a quick and hacky solution with sox that can be easily installed on any Linux distribution. sox in.wav -n trim 0 0.1 stats : newfile : restart 2>&1 | grep 'RMS lev dB' | cut -d' ' -f 7 This will return RMS levels for each 0.1 second chunk. Change in.wav to the input file and 0.1 if you require a different frame length.


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"So do I only use the sinc functions for the samples that are closest to my x value?" Yes, when you are truncating. "Is this what is meant by "windowed sinc"?" Yes. The sinc goes to infinity, calculating that is impractical. "How many samples should I go in each direction away from my x value?" The sinc diminishes the ...


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A spectrogram is a graphical time-scroll representation of the frequency components in a signal. Sometimes it's called a "waterfall", because that's what it looks like as it is computed and plotted in real time. The core math behind this is the FFT. A spectrogram generally shows the strength (or magnitude) of a range of frequency components in a ...


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Everything is possible with advanced technology, due diligence and perseverance. To discuss the means to reach your goals requires even more detailed description of target scenarios. If you have a pure tone -- I mean, a musically pure single note performed by a good musician with a quality instrument or an opera singer -- you can analyze this sound by ...


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After reading the linked article by Julius Smith, flipping the spectrum entirely as the OP is requesting is NOT the intention of that author. That article is shifting the spectrum to the left by only half a DFT bin as an alternate approach to the complexity of creating an analytic signal with the Hilbert Transform for purposes of making an octave band filter ...


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$$ y[n] = (-1)^n \cdot x[n] $$ This will flip the spectrum in linear frequency. Easy to do, easy to recover.


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You're trying to do the time warp dance. If you were copying the samples point by point, your playback time (destination) and your look up time (source) would be the same. If you wanted to speed it up by a factor of two(one octave), your lookup time (source location in the array) would be moving twice as fast as your sample time (location in your output ...


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As most of the answers already provided state, this is quite tricky and rather difficult to achieve faithful decomposition of the sound field. Since you are considering a pair of microphones you could consider two different methods to decompose the impinging sound field into idealized plane waves. Coincidence microphones: Here you have to use the magnitude ...


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Which algorithms can be used to "re-spatialize" this recording, i.e. try to virtually "move the microphones", and recreate a new stereo signal, for example with an AB mic positioning? In general, this is a beamforming "problem", but it cannot be done in exactly the way it is described here. With a setup like this, you can ...


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In general terms, you can convert the magnitudes and phases into complex numbers. See this reference. Once that's done, you can take the Inverse Discrete Fourier Transform to attempt to recover the audio. You haven't indicated weather or not you know how these files were made so there is no guarantee that applying such a direct method will work. In the ...


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